Your team already knows AI. What is missing is applying it at work
Your team already uses ChatGPT personally but not at work. When they try, they lose time fighting the output or settle for generic results. Generative AI is like driving: without an instructor and regular practice, the team moves at a crawl while competitors accelerate.
- 1Workflow assessment: we identify 3-5 weekly tasks where Claude delivers the most value for your team.
- 2Weekly sessions (60 min): a real case from the team, prompt engineering, templates they keep.
- 3Slack/WhatsApp support: your team asks us real questions between sessions.
- 4Workflow implementation: we build together the first 3 prompts or agents that live inside the operation.
- 5Monthly metrics: we measure hours saved, tasks automated, output delivered.
What you get that a course does not give you
This is not an isolated course or a one-off workshop. It is ongoing support inside the real context of your team.
Team, not individuals
Everyone comes together and learns in the real context of how the team works. The templates and workflows are built for that specific team.
Business context
The prompts and agents we build use your data and your processes. Not generic internet templates — solutions your team can apply the same day.
Monthly continuity
AI changes every month. Your team stays current because we stay with you, instead of handing over a manual and disappearing.
Online plus in person in Puebla
Sessions run over video, but when it helps we sit down with your team in Puebla. Especially useful for off-sites and kickoffs.
Casos de Éxito
Real teams that went from using AI personally to building their own solutions with Claude.
Warezom
We trained their team on Claude until they build their own internal platforms — customer follow-up, warranty management, and analysis of Odoo data — under our supervision.
From AI noob to AI pro: their team now ships its own successful projects
Para qué tipo de equipo
Tres frentes donde el retainer ha generado el salto más visible en equipos PyME.
Marketing
Consistent brand voice across channels, creative briefs in minutes, market research, editorial content generation, analysis of comments and reviews.
Operations
Automation of recurring reports, process documentation, first draft of customer replies, analysis of unstructured data, SOP generation.
Sales
Drafts of commercial proposals, personalized follow-ups, prospect research, call summaries, outreach content.
Preguntas Frecuentes
Lo que más nos preguntan empresas al evaluar este servicio.
How long does it take to see concrete results in my team?+
The first hours saved show up in week 2, when the team applies the first templates to their real work. The structural changes — automated workflows the team maintains on its own — settle between month 2 and month 3. That is why the model is monthly: the real adoption curve takes several weeks.
My team is not technical — can they adopt Claude without programming?+
Yes, and it is the most common case we handle. Claude is used in natural language, not by programming. Sessions focus on how to write clear instructions and how to check that the answer is useful. The more sophisticated workflows (agents connected to other apps) are built by us, and your team simply activates them when needed.
What kind of tasks can Claude improve in my team?+
Any task that involves writing, reading, summarizing, analyzing text, or structuring information. Real examples: drafting the first version of proposals, summarizing 50 customer reviews, generating monthly reports with narrative, translating and adapting content across markets, pulling insights from call transcripts. Purely operational tasks (moving data between systems) require integrations — we build those too, but they fall under the workflow scope.
What does a typical session look like?+
60 minutes over video call (or in person if we are in Puebla). The team brings a real case from their week and we work on it together: we identify what Claude can do with it, write the prompt live, iterate until the output is usable, and at the end the team keeps the saved template. Never abstract: always with client data and real cases.
Why Claude and not ChatGPT or another model?+
Claude (Anthropic) has three advantages for business use: better handling of long and complex instructions, very large context windows (you can paste whole documents without chunking them), and clearer enterprise usage policies. ChatGPT is not a bad model and we use it when it applies — but our specialization is Claude, which lets us get more value out of the tooling. The idea is not to lock you in: the team learns prompt engineering principles that apply to any model.
What happens if Claude changes or something better comes out?+
That is part of the retainer model. When Anthropic releases new capabilities (claude-code, agents, faster models), your team learns them in the next session at no extra cost. If a different model turns out to be better for a specific use case, we evaluate it together in a session. The retainer is not there to tie you to Claude — it is there to keep your team current with whatever works best.